Chronosphere is a cloud-native observability platform that controls metrics costs at scale with AI-driven data management and anomaly detection.
Chronosphere built its observability platform for scale economics: it gives platform teams control over which metrics, logs, and traces are stored, dramatically reducing observability spend in large Kubernetes environments. AI features power anomaly detection, trace analysis, and data-tiering recommendations that keep signal high and cost low. Born from the creators of Uber’s M3 metrics platform, it handles billions of time series in production. Large engineering organizations adopt Chronosphere to make observability affordable as infrastructure grows.
Chronosphere is built for the scale where observability pricing becomes a finance conversation: billions of time series, sprawling Kubernetes estates, and cardinality explosions that consume budgets. Its data-shaping controls let platform teams decide what is stored at what fidelity — governance that directly attacks cost — while AI anomaly detection keeps signal quality high on what remains. Trace analysis and service mapping handle microservice debugging at the same scale. The product’s pedigree (from Uber’s metrics platform) shows in architectural confidence at hyperscale. Implementation targets platform teams rather than individual developers, and the economics favor large deployments. For organizations where observability spend is outgrowing infrastructure spend, Chronosphere is the specialist instrument for regaining control without losing visibility.
Chronosphere sells enterprise subscriptions quoted based on data volume, retention, and platform scope, with pricing positioned against runaway observability costs. Buyers engage through sales with proof-of-value deployments on their own environments.
It is built for large platform and SRE teams running cloud-native infrastructure at scale where observability costs are a board-level issue. Organizations with billions of metrics points see the strongest ROI.
No. Chronosphere is an enterprise platform sold through sales engagements sized to data volume and scale. Buyers evaluate it through proof-of-value deployments measuring both detection quality and cost reduction.
Yes. Chronosphere is OpenTelemetry-compatible and exposes ingestion, query, and configuration APIs, letting platform teams automate data-shaping policies and integrate with incident and deployment workflows.
Compared with Datadog and New Relic, Chronosphere’s differentiator is cost governance at extreme scale. Versus Prometheus-based stacks, it adds enterprise management, long-term storage, and AI analysis without self-run complexity.